When leaders are tasked with assessing macro questions such as “how do we better meet demand?” or “how can we better manage capacity?” they’re at the same time expected to identify and operationalize answers to those questions. Answers come in the form of widespread and far-reaching decisions related to strategic paths, policies, partners, and more. But how can leaders be confident that the path chosen is the best one? This is especially challenging given that demand changes almost continuously, meaning so too does the optimal path for meeting it.
Digital Planning Twins are now providing leaders prescriptive and quantified insights that inform the optimal path forward amid multiple objectives and constraints. Here’s how FedEx Office partnered with Accenture and River Logic to apply it and make big strides in a short time.
Defining the Objective
FedEx Office is comprised of nearly 2,200 retail stores, 15,000 employees, 18 commercial print facilities, and a nationwide transportation fleet. Tom DeGreve, Managing Director of Production Strategy & Engineering for FedEx Office, supported by advisement from Pierre Mawet, Managing Director of Supply Chain & Operations at Accenture NA, set out to better understand the complexities of print for the company’s customers, costs associated with transportation and production, and how to best meet demand at any given time. Greater insight into these areas would inform operational improvement and resource adaptability for enhanced customer relationships and better business overall.
Finding the Right Approach
Initial optimization efforts at FedEx were rather narrowly focused. The starting point was a relatively small, internally driven, and more loosely structured approach that required a great deal of effort and explored several simulation-based methods. As the team sought to introduce more variables and more complexity to their models, it became increasingly difficult and impractical to assess them via Excel and other tools in place at the time. This difficulty served as a catalyst for finding a better approach.
By implementing a Digital Planning Twin, FedEx Office could create a constraint-based digital representation of their full value chain. This approach would incorporate all key functional components (commercial, operational, financial) to enable assessing a virtually limitless array of variables and options. After gaining internal buy-in as to its possibilities, a Digital Planning Twin was advanced by the company to create capability they could build on and gain more and more value over time.
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Biggest Challenge
Some organizations struggle with not having enough reliable data readily available to realize the full power of a Digital Planning Twin. This could be aggregate-only or unvalidated data that won’t accurately depict the interplay between variables such as capacity, assets, labor planning, and variable costs. FedEx Office, on the other hand, discovered that they initially incorporated so much data that it crashed their models. This triggered important conversations that centered on, as DeGreve explained, “how we think about the business.” In short, the team needed to find the right level of detail and, at the same time, not settle for a rudimentary aggregate.
With the Digital Planning Twin, FedEx Office now has a model that continuously runs a 10-day view of baseline down to the tens of thousands of interactions that take place every week. This provides a highly detailed view of behaviors across their overall system. It also incorporates seasonality, time elements, and other constraints to inform the best possible way to service demand at any given time. It’s a true replica of operations, not just an aggregate for a certain period.
From Insight to Action
Before its Digital Planning Twin was in place, decisions on service components like how to route orders were guided by mostly absolute policies. With Digital Planning Twin, FedEx Office is now able to identify conditions where deviations from those policies are warranted to enable higher profitability and a better customer experience. For example, current conditions may show delivery by 3 pm vs. 5 pm would mean significant differences in costs and resources. If 5 pm delivery is acceptable to the customer, they can a lower cost for the same quality service.
FedEx Office first pilots policy adjustments like those described above in a few markets and then expands them more widely as they prove their real-world value. In the short time their Digital Planning Twin has been active, they’ve been able to realize a solid ROI that will only grow. In a recent webcast, DeGreve cited one example, saying that “delivery from plants and back to stores is a significant annual spend – one we now believe we can cut by up to 45%.” That’s a big number and only represents the transportation portion of the service equation.
Source: https://www.supplychainbrief.com/?open-article-id=21290797&article-title=improving-capacity-planning-and-operations-with-a-digital-planning-twin&blog-domain=riverlogic.com&blog-title=river-logic